/// <summary>
/// Creating FeedForward - Neural Network
/// </summary>
/// <param name="memoryFolderName"></param>
/// <param name="networkStructure"></param>
/// <param name="testDatasetPath"></param>
/// <returns>Returns success result of network creating</returns>
public bool CreateNetwork(string memoryFolderName,
NetworkStructure networkStructure,
string testDatasetPath = null)
{
_networkStructure = networkStructure;
if (FileManager.CheckMemoryIntegrity(networkStructure, memoryFolderName))
{
try
{
_networkTeacher = new NetworksTeacher(networkStructure);
}
catch
{
return(false);
}
if (testDatasetPath != null)
{
_networkTeacher.TestVectors = FileManager.LoadTestDataset(testDatasetPath);
}
return(true);
}
else
{
return(false);
}
}
// TODO: Выделить структуру Extraction-зоны в отдельный объект
public void CreateNetwork(NetworkStructure networkStructure,
int netsCountInAssembly = 1,
string testDatasetsPath = null)
{
_fileManager = new FileManager(networkStructure);
// TODO: [WARP] Тут настраивается схема слоев convolution и pooling
Extractor extractor = new Extractor("cpcppp", CreateConvFiltersScheme());
_networkTeacher = new NetworksTeacher(extractor, networkStructure, netsCountInAssembly, _fileManager);
// TODO: Сделать тестовое, но по изображению
//if (testDatasetsPath != null)
//{
// _networkTeacher.TestVectors = _fileManager.LoadDatasets(testDatasetsPath);
//}
}